Predicting the age of ancient Thuja occidentalis on cliffs
In rocky, heterogeneous environments that support old-growth forests, the relationship between tree size and age is weaker than it is for trees growing in productive and homogeneous habitats. To assist in the management and conservation of ancient forests on rocky land of low productivity, it would...
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Veröffentlicht in: | Canadian journal of forest research 2008-12, Vol.38 (12), p.2923-2931 |
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creator | Matthes, Uta Kelly, Peter E Larson, Douglas W |
description | In rocky, heterogeneous environments that support old-growth forests, the relationship between tree size and age is weaker than it is for trees growing in productive and homogeneous habitats. To assist in the management and conservation of ancient forests on rocky land of low productivity, it would be useful if the relationships among age, environmental heterogeneity, and morphological variability could be understood and used to develop predictive models of longevity so that extensive core sampling of trees would not be required. Here we sampled 296 mature Thuja occidentalis L. growing on limestone cliffs along the Niagara Escarpment, southern Ontario, Canada. We measured a variety of site conditions and morphological traits, including age, which varied from 51 to 1316 years. We then used redundancy analysis and multiple regression to model the relationships among age, morphology, growth rate, and environment, resulting in quantitative models predicting tree age from four subsets of variables. We subsequently tested the models on 60 additional trees not used to build the models and found that they predicted up to 78% of the variation in actual tree age. This approach could be adopted for use in other forest types to predict the age of trees without using tree-ring analysis. |
doi_str_mv | 10.1139/X08-131 |
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To assist in the management and conservation of ancient forests on rocky land of low productivity, it would be useful if the relationships among age, environmental heterogeneity, and morphological variability could be understood and used to develop predictive models of longevity so that extensive core sampling of trees would not be required. Here we sampled 296 mature Thuja occidentalis L. growing on limestone cliffs along the Niagara Escarpment, southern Ontario, Canada. We measured a variety of site conditions and morphological traits, including age, which varied from 51 to 1316 years. We then used redundancy analysis and multiple regression to model the relationships among age, morphology, growth rate, and environment, resulting in quantitative models predicting tree age from four subsets of variables. We subsequently tested the models on 60 additional trees not used to build the models and found that they predicted up to 78% of the variation in actual tree age. This approach could be adopted for use in other forest types to predict the age of trees without using tree-ring analysis.</description><identifier>ISSN: 0045-5067</identifier><identifier>EISSN: 1208-6037</identifier><identifier>DOI: 10.1139/X08-131</identifier><identifier>CODEN: CJFRAR</identifier><language>eng</language><publisher>Ottawa, ON: National Research Council of Canada</publisher><subject>Age ; Aging ; Biological and medical sciences ; cliff faces ; cliffs ; Conservation ; dolomitic limestone ; environmental factors ; Escarpments ; Forest management ; forest trees ; Forestry ; Fundamental and applied biological sciences. Psychology ; Growth ; Heterogeneity ; Limestone ; Niagara escarpment ; old-growth forests ; Plant growth ; plant morphology ; prediction ; Prediction models ; Regression analysis ; statistical models ; stem form ; Thuja occidentalis ; tree age ; tree growth ; Trees</subject><ispartof>Canadian journal of forest research, 2008-12, Vol.38 (12), p.2923-2931</ispartof><rights>2009 INIST-CNRS</rights><rights>COPYRIGHT 2008 NRC Research Press</rights><rights>Copyright National Research Council of Canada Dec 2008</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c575t-212f962a964603d9a7222323cc7734d5b832613b6a676c00d3a43e1d40741113</citedby><cites>FETCH-LOGICAL-c575t-212f962a964603d9a7222323cc7734d5b832613b6a676c00d3a43e1d40741113</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,776,780,27901,27902</link.rule.ids><backlink>$$Uhttp://pascal-francis.inist.fr/vibad/index.php?action=getRecordDetail&idt=21103727$$DView record in Pascal Francis$$Hfree_for_read</backlink></links><search><creatorcontrib>Matthes, Uta</creatorcontrib><creatorcontrib>Kelly, Peter E</creatorcontrib><creatorcontrib>Larson, Douglas W</creatorcontrib><title>Predicting the age of ancient Thuja occidentalis on cliffs</title><title>Canadian journal of forest research</title><addtitle>Revue canadienne de recherche forestière</addtitle><description>In rocky, heterogeneous environments that support old-growth forests, the relationship between tree size and age is weaker than it is for trees growing in productive and homogeneous habitats. To assist in the management and conservation of ancient forests on rocky land of low productivity, it would be useful if the relationships among age, environmental heterogeneity, and morphological variability could be understood and used to develop predictive models of longevity so that extensive core sampling of trees would not be required. Here we sampled 296 mature Thuja occidentalis L. growing on limestone cliffs along the Niagara Escarpment, southern Ontario, Canada. We measured a variety of site conditions and morphological traits, including age, which varied from 51 to 1316 years. We then used redundancy analysis and multiple regression to model the relationships among age, morphology, growth rate, and environment, resulting in quantitative models predicting tree age from four subsets of variables. We subsequently tested the models on 60 additional trees not used to build the models and found that they predicted up to 78% of the variation in actual tree age. This approach could be adopted for use in other forest types to predict the age of trees without using tree-ring analysis.</description><subject>Age</subject><subject>Aging</subject><subject>Biological and medical sciences</subject><subject>cliff faces</subject><subject>cliffs</subject><subject>Conservation</subject><subject>dolomitic limestone</subject><subject>environmental factors</subject><subject>Escarpments</subject><subject>Forest management</subject><subject>forest trees</subject><subject>Forestry</subject><subject>Fundamental and applied biological sciences. Psychology</subject><subject>Growth</subject><subject>Heterogeneity</subject><subject>Limestone</subject><subject>Niagara escarpment</subject><subject>old-growth forests</subject><subject>Plant growth</subject><subject>plant morphology</subject><subject>prediction</subject><subject>Prediction models</subject><subject>Regression analysis</subject><subject>statistical models</subject><subject>stem form</subject><subject>Thuja occidentalis</subject><subject>tree age</subject><subject>tree growth</subject><subject>Trees</subject><issn>0045-5067</issn><issn>1208-6037</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2008</creationdate><recordtype>article</recordtype><recordid>eNqV0ltrFDEUAOAgCq5V_AkOgorC1Nwm2fGtFC-FomJX8C2cZpLZLLPJNpmB-u89ZUrran2QPOTCl5Pk5BDylNFDxkT79gdd1kywe2TBOA4VFfo-WVAqm7qhSj8kj0rZUEqFEnRB3n3Nrgt2DLGvxrWroHdV8hVEG1wcq9V62kCVrA0dTmEIpUqxskPwvjwmDzwMxT257g_I6sP71fGn-vTLx5Pjo9PaNroZa864bxWHVkm8S9eC5pwLLqzVWsiuOV8Krpg4V6C0spR2AqRwrJNUS4YvOiAv57C7nC4mV0azDcW6YYDo0lQMp41iXGiEz_-AmzTliFczXCCSS6UQ1TPqYXAmRJ_GDLZ30WUYUnQ-4PIRa7latpi_26B73u7ChfkdHd6BsHVuG-ydUV_vbUAzusuxh6kUc3L27T_s5337arY2p1Ky82aXwxbyT8OouaoOg9VhsDpQvrhOFhQLg89XP15uOGcM64br2-zHbLMrDrJd36jLOZjZdR7hm3_Dv09_NmMPyUCf8eTvZ5wyQVmjZSu1-AX-CtXK</recordid><startdate>20081201</startdate><enddate>20081201</enddate><creator>Matthes, Uta</creator><creator>Kelly, Peter E</creator><creator>Larson, Douglas W</creator><general>National Research Council of Canada</general><general>NRC Research Press</general><general>Canadian Science Publishing NRC Research Press</general><scope>FBQ</scope><scope>IQODW</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>ISN</scope><scope>ISR</scope><scope>7SN</scope><scope>7SS</scope><scope>7T7</scope><scope>8FD</scope><scope>C1K</scope><scope>FR3</scope><scope>P64</scope><scope>RC3</scope><scope>U9A</scope></search><sort><creationdate>20081201</creationdate><title>Predicting the age of ancient Thuja occidentalis on cliffs</title><author>Matthes, Uta ; Kelly, Peter E ; Larson, Douglas W</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c575t-212f962a964603d9a7222323cc7734d5b832613b6a676c00d3a43e1d40741113</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2008</creationdate><topic>Age</topic><topic>Aging</topic><topic>Biological and medical sciences</topic><topic>cliff faces</topic><topic>cliffs</topic><topic>Conservation</topic><topic>dolomitic limestone</topic><topic>environmental factors</topic><topic>Escarpments</topic><topic>Forest management</topic><topic>forest trees</topic><topic>Forestry</topic><topic>Fundamental and applied biological sciences. Psychology</topic><topic>Growth</topic><topic>Heterogeneity</topic><topic>Limestone</topic><topic>Niagara escarpment</topic><topic>old-growth forests</topic><topic>Plant growth</topic><topic>plant morphology</topic><topic>prediction</topic><topic>Prediction models</topic><topic>Regression analysis</topic><topic>statistical models</topic><topic>stem form</topic><topic>Thuja occidentalis</topic><topic>tree age</topic><topic>tree growth</topic><topic>Trees</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Matthes, Uta</creatorcontrib><creatorcontrib>Kelly, Peter E</creatorcontrib><creatorcontrib>Larson, Douglas W</creatorcontrib><collection>AGRIS</collection><collection>Pascal-Francis</collection><collection>CrossRef</collection><collection>Gale In Context: Canada</collection><collection>Gale In Context: Science</collection><collection>Ecology Abstracts</collection><collection>Entomology Abstracts (Full archive)</collection><collection>Industrial and Applied Microbiology Abstracts (Microbiology A)</collection><collection>Technology Research Database</collection><collection>Environmental Sciences and Pollution Management</collection><collection>Engineering Research Database</collection><collection>Biotechnology and BioEngineering Abstracts</collection><collection>Genetics Abstracts</collection><jtitle>Canadian journal of forest research</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Matthes, Uta</au><au>Kelly, Peter E</au><au>Larson, Douglas W</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Predicting the age of ancient Thuja occidentalis on cliffs</atitle><jtitle>Canadian journal of forest research</jtitle><addtitle>Revue canadienne de recherche forestière</addtitle><date>2008-12-01</date><risdate>2008</risdate><volume>38</volume><issue>12</issue><spage>2923</spage><epage>2931</epage><pages>2923-2931</pages><issn>0045-5067</issn><eissn>1208-6037</eissn><coden>CJFRAR</coden><abstract>In rocky, heterogeneous environments that support old-growth forests, the relationship between tree size and age is weaker than it is for trees growing in productive and homogeneous habitats. To assist in the management and conservation of ancient forests on rocky land of low productivity, it would be useful if the relationships among age, environmental heterogeneity, and morphological variability could be understood and used to develop predictive models of longevity so that extensive core sampling of trees would not be required. Here we sampled 296 mature Thuja occidentalis L. growing on limestone cliffs along the Niagara Escarpment, southern Ontario, Canada. We measured a variety of site conditions and morphological traits, including age, which varied from 51 to 1316 years. We then used redundancy analysis and multiple regression to model the relationships among age, morphology, growth rate, and environment, resulting in quantitative models predicting tree age from four subsets of variables. We subsequently tested the models on 60 additional trees not used to build the models and found that they predicted up to 78% of the variation in actual tree age. This approach could be adopted for use in other forest types to predict the age of trees without using tree-ring analysis.</abstract><cop>Ottawa, ON</cop><pub>National Research Council of Canada</pub><doi>10.1139/X08-131</doi><tpages>9</tpages></addata></record> |
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subjects | Age Aging Biological and medical sciences cliff faces cliffs Conservation dolomitic limestone environmental factors Escarpments Forest management forest trees Forestry Fundamental and applied biological sciences. Psychology Growth Heterogeneity Limestone Niagara escarpment old-growth forests Plant growth plant morphology prediction Prediction models Regression analysis statistical models stem form Thuja occidentalis tree age tree growth Trees |
title | Predicting the age of ancient Thuja occidentalis on cliffs |
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